The role of fault network geometry on the complexity of seismic cycles in the Apennines

Rodriguez Piceda, Constanza; Mildon, Zoë K.; Andrews, Billy J.; Yin, Yifan; Ampuero, Jean-Paul; van den Ende, Martijn; Sgambato, Claudia; Galvez, Percy

doi:10.5194/egusphere-2025-4694

Preprints

https://doi.org/10.5194/egusphere-2025-4694

Preprints

08 Oct 2025

| 08 Oct 2025

Status: this preprint is open for discussion and under review for Solid Earth (SE).

The role of fault network geometry on the complexity of seismic cycles in the Apennines

Constanza Rodriguez Piceda, Zoë K. Mildon, Billy J. Andrews, Yifan Yin, Jean-Paul Ampuero, Martijn van den Ende, Claudia Sgambato, and Percy Galvez

Abstract. Estimating the recurrence intervals and magnitudes of earthquakes for a given fault is essential for seismic hazard assessment but often challenging due to the long recurrence times of large earthquakes. Fault network geometry (i.e. spatial arrangement between faults) plays a key role in modulating stress interactions and, consequently, earthquake recurrence and magnitude. Here, we investigate these effects of fault network geometry using earthquake cycle models to generate numerous earthquakes on two different networks of normal faults in Italy: the Central Apennines, characterised by a wide network of faults offset across strike, and the Southern Apennines, a narrow fault network where faults are predominantly arranged along strike. For each region, we ran an earthquake cycle simulation on systems of seven normal faults generating approximately 150 earthquakes. In the Central Apennines, co-seismic stress transfer between faults promotes more heterogeneous stress, more partial ruptures, greater Mw variability and less periodic behaviour of large earthquakes (coefficient of variation of recurrence time, CV 0.1–0.9). In contrast, faults in the Southern Apennines experience more homogeneous stress loading, leading to a higher proportion of full-fault ruptures with more regular recurrence intervals (CV 0–0.4). In both fault networks, high long-term slip rate amplifies the effects of fault interactions: faults with higher long-term slip rate are more sensitive to positive stress perturbations from nearby faults compared to slower-moving faults. These results highlight that incorporating stress interactions from fault network geometry into seismic hazard models is particularly important for networks of faults offset across strike, where rupture behaviour is more variable.

Received: 23 Sep 2025 – Discussion started: 08 Oct 2025

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.

Download & links

Constanza Rodriguez Piceda, Zoë K. Mildon, Billy J. Andrews, Yifan Yin, Jean-Paul Ampuero, Martijn van den Ende, Claudia Sgambato, and Percy Galvez

Status: open (until 30 Dec 2025)

Post a comment Subscribe to comment alert

RC1:
'Comment on egusphere-2025-4694', Anonymous Referee #1, 01 Dec 2025 reply
I want to acknowledge the opportunity to review this manuscript. The research is pertinent as it addresses important questions of earthquake behavior complexities in fault networks. The experimental set up is appropriate and methods are novel, as earthquake cycle simulators are currently at the frontier of earthquake science. Formally, the paper is very well written, results and discussions are clear, and the figures are of excellent quality. I have only a few minor comments:
Some of the reasoning given for the exclusion of three faults of the Central Apennines is unconvincing and speculative, particularly the argument made about the minor contribution of these faults to the regional seismic hazard (lines 143-144). If the purpose of the study is to examine the influence of fault network geometry, the slow slip rates should not be a condition for exclusion. First, the impact on the hazard will depend on the target probability of exceedance (i.e., on the purpose of the hazard assessment). Second, their contribution to the hazard might not be straightforward, especially in a complex fault network context. That is, the activity of these faults might still impact earthquake cycles of nearby faults independently of their low activity rates, thereby affecting the rates of earthquakes and behavior within the system. Consider adapting the tone of this justification.

The Alburni fault depth is limited at 3km to avoid intersection with the Vallo di Diano fault. This is a very short depth to effectively generate earthquakes. In fact, in your study this fault does not generate earthquakes. Have you considered resolving this structure better at depth? For instance, propagating it up to the intersection with the Vallo di Diano fault. Otherwise, I do not see the point of including this fault.

Line 247: “fault sin” should be “faults in”

For the analyses in figure 4, I suggest to compare the MFDs obtained with the simulator with analytical MFDs based on the seismic moment rate balancing. Given that your models do not generate multi-fault ruptures, such a comparison would be fair and would be useful to clearly determine what are the differences/improvements of your physics-based approach against more simpler, but widely used, approaches in seismic hazard. Physics-based models are expensive and not always easy to implement, so this exercise might help you further justify why we need them in favor of less expensive approaches that might provide similar occurrence statistics.

In the paragraph starting in line 317, you mention that fault networks with fewer partially overlapping across-strike nearby faults tend to nucleate earthquakes near the fault tips. In the appendix, you also mention that QDYN uses the back-slip approach to apply loading on faults. The back-slip approach is known to generate stress singularities near the fault tips resulting in unrealistic earthquake nucleations in these fault regions, especially when slip rates are not tapered (as your case). I was wondering to what extent these fault-tip nucleations in more isolated fault systems like the Southern Apennines can be linked to effects of the back-slip loading? Does QDYN or your post-simulation analysis consider any internal correction to mitigate this effect?

In figure 9, the mean recurrence time dashed line is grey in the figure but black in the legend. Consider homogenization.

Across-strike interaction index is referred to as both AI and GI in the manuscript (e.g., line 432). Consider homogenization.

Line 435 should say Central Apennines? Spearman correlation indices in Table F1 indicate poorer correlation for the Central Apennines than the Southern.

I am curious to know a bit more on why the simulator does not produce multi-fault ruptures in the system. There are other quasi-dynamic simulators (RSQSim or MCQsim) that are demonstrating to produce such ruptures in across-strike fault systems, so I am not sure how the quasi-dynamic approximation in QDYN is inhibiting this behavior. Does it have to do with the specific friction/stressing parametrization of your models? Have you verified that other friction parameters also inhibit multi-fault ruptures? I think the paper should discuss more details on this topic?

Concerning the preferred nucleation locations discussed in section 5.4, I suggest discussing the role of including fault-specific geometric complexities in future models as well. Complex, non-planar, fault geometries (e.g., variable dip, fault roughness) would most likely impact earthquake nucleation and rupture behavior significantly in the studied fault system networks.

Reply
Citation: https://doi.org/10.5194/egusphere-2025-4694-RC1
RC2: 'Comment on egusphere-2025-4694', Anonymous Referee #2, 09 Dec 2025 reply

The manuscript is very well written, clear, and logically structured, with nice figures that support the scientific narrative. From the beginning, the objectives are clear: the abstract and introduction make it immediately evident that the aim is to investigate how network geometry of a fault system influences the seismic cycles. The literature is well selected and synthesised and the figures are well composed, readable, and helpful.
While the manuscript is strong, there are a few aspects where additional clarification could enhance its robustness.
First, regarding the scaling factor of ×100 adopted for numerical reasons: although the explanation is present, the paragraph is quite dense, and not all readers familiar with QDYN modelling will immediately recognise the implications of this choice. It would be helpful if the authors could elaborate on why this specific scaling factor was chosen rather than another value, and, if available, include a brief robustness check showing results obtained with a different scaling factor (e.g. ×50 or ×150). This would provide readers with a clearer sense of the sensitivity of the results to this numerical adaptation.
A second point concerns the exclusion of the three smaller faults (Parasano–Pescina, Tremonti, and San Sebastiano) from the Central Apennines network. While I understand the need to reduce intersections and avoid numerical instabilities, the justification feels somewhat incomplete given the stated aim of analysing system-scale behaviour. Even relatively short or low-slip-rate segments may influence the connectivity of the network and the topology of rupture paths. Previous studies have shown that such linking structures can significantly affect recurrence intervals, segmentation patterns, and fault-to-fault interactions. For these reasons, it would be beneficial for the authors to provide a clearer rationale for their exclusion and, if any preliminary sensitivity tests were performed (even qualitatively), to briefly comment on whether the presence or absence of these segments modifies the system behaviour. A short assessment of this point would greatly strengthen confidence in the selected network geometry.
A related and important limitation is that the current numerical framework does not allow ruptures to propagate across fault intersections (namely multi-fault ruptures). In the tectonic context of the Central Apennines, multi-fault ruptures for example have been proposed to explain several aspects of the paleoseismic record. Recent fault-based PSHA studies have also shown that relaxing segmentation rules improves consistency with observed rupture histories in the region. A more explicit acknowledgement of how this limitation affects the interpretation of the results would be valuable. In particular, discussing whether this might influence the reported patterns of recurrence variability and complexity would help readers understand the scope of the conclusions. Even a brief paragraph in the Discussion would make this aspect clearer.
Finally, in the last part of the manuscript, the implications for fault-based seismic hazard are interesting but could be better articulated. While the scientific insights into geometric control on network behaviour are compelling, the practical consequences for hazard modelling remain somewhat unclear. Probabilistic fault-based models typically require magnitudes, recurrence intervals, rupture dimensions, and structured epistemic uncertainties. It is not yet evident how the results of the present SEAS models can be translated into these quantities. For example, can the synthetic recurrence behaviour be used to inform logic-tree branches? Do the simulated ruptures provide magnitude–frequency constraints? Or should the results be interpreted mainly as conceptual insights into fault-network dynamics? Clarifying what aspects of the modelling are directly actionable for PSHA, and what aspects remain at the conceptual or physics-modelling level, would significantly improve the applied relevance of the work.
Overall, this is a well-written manuscript with high-quality figures and a clear narrative. My comments do not concern the core results, which I find convincing, but rather focus on three aspects where additional clarification or discussion would strengthen the robustness and applicability of the study: the justification for excluding three faults from the Central Apennines network, the implications of not allowing multi-fault ruptures, and the practical relevance of the modelling outcomes for fault-based seismic hazard assessments.

Reply

Citation: https://doi.org/10.5194/egusphere-2025-4694-RC2

Constanza Rodriguez Piceda, Zoë K. Mildon, Billy J. Andrews, Yifan Yin, Jean-Paul Ampuero, Martijn van den Ende, Claudia Sgambato, and Percy Galvez

Viewed

Total article views: 320 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
213	92	15	320	16	16

HTML: 213
PDF: 92
XML: 15
Total: 320
BibTeX: 16
EndNote: 16

Views and downloads (calculated since 08 Oct 2025)

Month	HTML	PDF	XML	Total
Oct 2025	118	40	8	166
Nov 2025	65	44	5	114
Dec 2025	30	8	2	40

Cumulative views and downloads (calculated since 08 Oct 2025)

Month	HTML	PDF	XML	Total
Oct 2025	118	40	8	166
Nov 2025	65	44	5	114
Dec 2025	30	8	2	40

Viewed (geographical distribution)

Total article views: 316 (including HTML, PDF, and XML) Thereof 316 with geography defined and 0 with unknown origin.

Country	#	Views	%

Latest update: 09 Dec 2025

Short summary

We investigate how the spatial arrangement of normal faults in the Italian Apennines affects earthquake timing and size. Computer-based models show that wide networks with faults offset across-strike produce more irregular and variable earthquakes, while narrow networks with fewer across-strike faults lead to more regular events. Faster-moving faults are more sensitive to nearby positive stress interactions, highlighting the need to consider fault geometry in seismic hazard assessments.


Total:	0
HTML:	0
PDF:	0
XML:	0